As is well-know the N-P test as long the Null Hypotheses (H0) is nullified automatically the Alternative one (H1) is chosen as preferable. PFP as a rather different behavior: Given a set of k parameters and their Critical Values the Outputs/Responses in accordance with the Distributions under test are classified binary, 0, 1, in accordance we found *accept* or reject. A different kind of optional strategy, I think, because is a simultaneous checking procedure where the decision depends on the frequencies found and, contrarily to N-P scheme, chosen *by defect* Hypotheses are absent.